Articles | Volume 12, issue 8
https://doi.org/10.5194/gmd-12-3523-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-12-3523-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
13 Aug 2019
Development and technical paper |
| 13 Aug 2019
| 13 Aug 2019
A parallel workflow implementation for PEST version 13.6 in high-performance computing for WRF-Hydro version 5.0: a case study over the midwestern United States
Jiali Wang
CORRESPONDING AUTHOR
Environmental Science Division, Argonne National Laboratory, 9700
South Cass Avenue, Lemont, IL 60439, USA
Cheng Wang
Environmental Science Division, Argonne National Laboratory, 9700
South Cass Avenue, Lemont, IL 60439, USA
Vishwas Rao
Mathematics and Computer Science Division, Argonne National Laboratory, 9700 South Cass Avenue, Lemont, IL 60439, USA
Andrew Orr
Environmental Science Division, Argonne National Laboratory, 9700
South Cass Avenue, Lemont, IL 60439, USA
Eugene Yan
Environmental Science Division, Argonne National Laboratory, 9700
South Cass Avenue, Lemont, IL 60439, USA
Environmental Science Division, Argonne National Laboratory, 9700
South Cass Avenue, Lemont, IL 60439, USA
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20 citations as recorded by crossref.
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- Harnessing high-performance computing and job scheduling for improving SWAT calibration and uncertainty analysis T. Dang et al. https://doi.org/10.1080/02626667.2026.2666375
- Impact on discharge modelling using different spatial and temporal resolution scenarios in South of Chile I. Fustos et al. https://doi.org/10.1016/j.jsames.2022.103727
- Assessment of the Impact of Spatial Variability on Streamflow Predictions Using High-Resolution Modeling and Parameter Estimation: Case Study of Geumho River Catchment, South Korea B. Kim et al. https://doi.org/10.3390/w16040591
- Toward Improved Regional Hydrological Model Performance Using State‐Of‐The‐Science Data‐Informed Soil Parameters C. Li et al. https://doi.org/10.1029/2023WR034431
- Impact of Fully Coupled Hydrology-Atmosphere Processes on Atmosphere Conditions: Investigating the Performance of the WRF-Hydro Model in the Three River Source Region on the Tibetan Plateau, China G. Li et al. https://doi.org/10.3390/w13233409
- Projected changes in extreme streamflow and inland flooding in the mid-21st century over Northeastern United States using ensemble WRF-Hydro simulations S. Pal et al. https://doi.org/10.1016/j.ejrh.2023.101371
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- MFIT 1.0.0: Multi-Flow Inversion of Tracer breakthrough curves in fractured and karst aquifers J. Bodin https://doi.org/10.5194/gmd-13-2905-2020
- Assessing the Impact of Parameter Sensitivity and Multi-Configurational Ensembles of WRF-Hydro Model on Simulated Hydro-Meteorological Variables—A Multifaceted Evaluation over Krishna River Basin of India S. Sarkar & P. Lakshmikanthan https://doi.org/10.1007/s00024-025-03909-6
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- Modeling the climate change impact on hydroclimate fluxes over the Beas basin using a high-resolution glacier-atmosphere-hydrology coupled setup A. Dixit et al. https://doi.org/10.1016/j.jhydrol.2023.130219
- Diurnal cycle of surface energy fluxes in high mountain terrain: High‐resolution fully coupled atmosphere‐hydrology modelling and impact of lateral flow Z. Zhang et al. https://doi.org/10.1002/hyp.14454
20 citations as recorded by crossref.
- Improving WRF‐Hydro runoff simulations of heavy floods through the sea surface temperature fields with higher spatio‐temporal resolution B. Kilicarslan et al. https://doi.org/10.1002/hyp.14338
- Augmentation of WRF-Hydro to simulate overland-flow- and streamflow-generated debris flow susceptibility in burn scars C. Li et al. https://doi.org/10.5194/nhess-22-2317-2022
- The influence of lateral flow on land surface fluxes in southeast Australia varies with model resolution A. Devanand et al. https://doi.org/10.5194/hess-29-4491-2025
- A Seasonal to Decadal Calibration of 1990–2100 Eastern Canadian Freshwater Discharge Simulations by Observations, Data Models, and Neural Networks R. Danielson et al. https://doi.org/10.1080/07055900.2025.2521502
- Fast Computer Model Calibration using Annealed and Transformed Variational Inference D. Cho et al. https://doi.org/10.1080/10618600.2024.2374962
- Flood frequency sampling error: insights from regional analysis, stochastic storm transposition, and physics-based modeling M. Abbasian et al. https://doi.org/10.1016/j.jhydrol.2025.133802
- Towards the construction of representative regional hydro(geo)logical numerical models: Modelling the upper Danube basin as a starting point E. Pujades et al. https://doi.org/10.3389/feart.2023.1061420
- Harnessing high-performance computing and job scheduling for improving SWAT calibration and uncertainty analysis T. Dang et al. https://doi.org/10.1080/02626667.2026.2666375
- Impact on discharge modelling using different spatial and temporal resolution scenarios in South of Chile I. Fustos et al. https://doi.org/10.1016/j.jsames.2022.103727
- Assessment of the Impact of Spatial Variability on Streamflow Predictions Using High-Resolution Modeling and Parameter Estimation: Case Study of Geumho River Catchment, South Korea B. Kim et al. https://doi.org/10.3390/w16040591
- Toward Improved Regional Hydrological Model Performance Using State‐Of‐The‐Science Data‐Informed Soil Parameters C. Li et al. https://doi.org/10.1029/2023WR034431
- Impact of Fully Coupled Hydrology-Atmosphere Processes on Atmosphere Conditions: Investigating the Performance of the WRF-Hydro Model in the Three River Source Region on the Tibetan Plateau, China G. Li et al. https://doi.org/10.3390/w13233409
- Projected changes in extreme streamflow and inland flooding in the mid-21st century over Northeastern United States using ensemble WRF-Hydro simulations S. Pal et al. https://doi.org/10.1016/j.ejrh.2023.101371
- Development of a calibration approach using DNDC and PEST for improving estimates of management impacts on water and nutrient dynamics in an agricultural system A. Bhattarai et al. https://doi.org/10.1016/j.envsoft.2022.105494
- MFIT 1.0.0: Multi-Flow Inversion of Tracer breakthrough curves in fractured and karst aquifers J. Bodin https://doi.org/10.5194/gmd-13-2905-2020
- Assessing the Impact of Parameter Sensitivity and Multi-Configurational Ensembles of WRF-Hydro Model on Simulated Hydro-Meteorological Variables—A Multifaceted Evaluation over Krishna River Basin of India S. Sarkar & P. Lakshmikanthan https://doi.org/10.1007/s00024-025-03909-6
- Computer Model Calibration with Time Series Data Using Deep Learning and Quantile Regression S. Bhatnagar et al. https://doi.org/10.1137/20M1382581
- Land-Use and Land Cover Is Driving Factor of Runoff Yield: Evidence from A Remote Sensing-Based Runoff Generation Simulation C. Xu et al. https://doi.org/10.3390/w14182854
- Modeling the climate change impact on hydroclimate fluxes over the Beas basin using a high-resolution glacier-atmosphere-hydrology coupled setup A. Dixit et al. https://doi.org/10.1016/j.jhydrol.2023.130219
- Diurnal cycle of surface energy fluxes in high mountain terrain: High‐resolution fully coupled atmosphere‐hydrology modelling and impact of lateral flow Z. Zhang et al. https://doi.org/10.1002/hyp.14454
Saved (final revised paper)
Latest update: 30 Jul 2026
Short summary
WRF-Hydro needs to be calibrated to optimize its output with respect to observations. However, when applied to a relatively large domain, both WRF-Hydro simulations and calibrations require intensive computing resources and are best performed in parallel. This study ported an independent calibration tool (parameter estimation tool – PEST) to high-performance computing clusters and adapted it to work with WRF-Hydro. The results show significant speedup for model calibration.
WRF-Hydro needs to be calibrated to optimize its output with respect to observations. However,...
